Introduction
The recent decline in average session duration for new Bumble users from 15 minutes to 8 minutes over the past month is a concerning trend that requires immediate attention. This significant drop could impact user engagement, retention, and ultimately, the app's success. I'll approach this issue systematically, focusing on identifying potential root causes, validating hypotheses, and developing both short-term and long-term solutions.
Framework overview
This analysis follows a structured approach covering issue identification, hypothesis generation, validation, and solution development.
Step 1
Clarifying Questions (3 minutes)
Why it matters: Recent changes could directly impact user behavior. Expected answer: Yes, we launched a new matching algorithm. Impact on approach: If confirmed, we'd focus on the algorithm's effects on user experience.
Why it matters: Helps identify if the issue is universal or specific to certain user types. Expected answer: The decline is more pronounced among users aged 18-24. Impact on approach: We'd tailor our investigation and solutions to this age group's preferences and behaviors.
Why it matters: Ensures we're comparing apples to apples in our analysis. Expected answer: No changes in metric calculation. Impact on approach: If confirmed, we can rule out measurement issues and focus on actual user behavior changes.
Why it matters: External influences could be driving user behavior changes. Expected answer: A major competitor launched a new feature last month. Impact on approach: We'd need to assess how this competitive move might be affecting our user engagement.
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